Although water is considered a renewable resource, there is only a fixed amount of water available. No additional water can be made, and we cannot easily control how fast water is recycled or in what form it will appear and where. With expected growth in the world’s population and economy, the same amount of water must supply more needs. Taking into account climate change projections and water-related environmental stresses, even less water might be available for human uses. People will need to decide how to serve a multitude of water needs. This dissertation uses the Southern Nevada Water Authority’s (SNWA) Groundwater Development Project to investigate how water policy designs handle the challenges of meeting urban and rural as well as human and ecological water needs when allocating scarce water supplies. The Southern Nevada Water Authority (SNWA) plans to build a pipeline to transfer groundwater from five rural basins in northeastern Nevada 300 miles south to the Las Vegas metropolitan area in Southern Nevada. SNWA has asked the Nevada State Engineer to approve its water right applications to develop and use groundwater from these rural basins. One of the basins, Snake Valley, straddles the border between Nevada and Utah. An interstate agreement allocating the groundwater between the two states is required before the State Engineer can approve water rights that would be diverted from Snake Valley. We found that policy debates and people’s rationales for how water should be allocated revolved around disagreements over beneficial use. In addition, water agreements need to be designed so that the risks from hydrologic uncertainties and impacts from other users are also apportioned clearly and equitably. Policy designs are purposefully crafted and have enormous impact, yet analysis of the actual contents of policies and their societal impacts has not received adequate attention within the policy sciences. The significance of this research is that it focuses on the foundational principles and rules for the allocation of scarce water resources that must necessarily balance urban and rural interests as well as human and environmental needs.

The Pahrump Band of Southern Paiute is an Indigenous group in southern Nevada that is not formally acknowledged by the United States government. This status was in part created by the production of space within the colonial system, through both cartographic and written texts. This thesis examines both the process of colonial space making around the Pahrump Band, and exposes the problems created by this process. Finally, a discussion is offered as to the value of re-presenting the spaces of the Pahrump Band in order to achieve political participation.

Contrary to popular belief, the L.A. region is more of a desert than a tropical oasis. Little rainfall during the winter months and practically no rainfall during the summer months is characteristic of Southern California’s desert-like weather patterns. Due to these low precipitation levels, water is considered the most important commodity in the Los Angeles region. Prior to 1900, the inhabitants of this area were fully aware of the importance of water. Most settlements were established near water sources and had adopted various techniques and constructed small-scale dams to conserve and reuse rainwater. Yet these measures were not sufficient to sustain large populations during drought conditions. Most settlers were forced to seek other areas where more reliable sources of water were found. The construction of early engineering feats like the Los Angeles aqueduct quickly changed prior perceptions of the region’s potential. Such systems allowed for cheap and previously inaccessible water to flow to the abundant land, spurring an unprecedented population and agricultural boom. For decades, the construction of more aqueducts and canals provided a sufficient amount of water to meet the demand in the region’s growing agricultural and financial economy. As the abundance of land and favorable weather attracted more businesses and industries into the region, more and more homes were built to accommodate the workforce. By 1936, the Hoover Dam had been built and California had signed and agreed to the Colorado River Compact, which granted Southern California 4.4 million acre-feet annually of the Colorado River’s water. As a result, relatively cheap water was able to meet the demands, thus catapulting California’s agricultural industry and residential development.

Recurrence rate is often used to describe volcanic activity. There are numerous documented ex- amples of non-constant recurrence rate (e.g. Dohrenwend et al., 1984; Condit and Connor, 1996; Cronin et al., 2001; Bebbington and Cronin, 2011; Bevilacqua, 2015), but current techniques for calculating recurrence rate are unable to fully account for temporal changes in recurrence rate. A local–window recurrence rate model, which allows for non-constant recurrence rate, is used to calculate recurrence rate from an age model consisting of estimated ages of volcanic eruption from a Monte Carlo simulation. The Monte Carlo age assignment algorithm utilizes paleomagnetic and stratigraphic information to mask invalid ages from the radiometric date, represented as a Gaussian probability density function. To verify the age assignment algorithm, data from Heizler et al. (1999) for Lathrop Wells is modeled and compared. Synthetic data were compared with expected results and published data were used for cross comparison and verification of recurrence rate and volume flux calculations. The latest recurrence rate fully constrained by the data is reported, based upon data provided in the referenced paper: Cima Volcanic Field, 33 +55/-14 Events per Ma (Dohren- wend et al., 1984), Cerro Negro Volcano, 0.29 Events per Year (Hill et al., 1998), Southern Nevada Volcanic Field, 4.45 +1.84/-0.87 (Connor and Hill, 1995) and Arsia Mons, Mars, 0.09 +0.14/-0.06 Events per Ma (Richardson et al., 2015). The local–window approach is useful for 1) identifying trends in recurrence rate and 2) providing the User the ability to choose the best median recurrence rate and 90% confidence interval with respect to temporal clustering.